Raise NotImplementedError for Categoricals with timezones (#14032)

Currently `cudf.from_pandas` with a pandas Categorical with datetimetz type will drop the timezone information (due to pyarrow)

```python
In [5]: import pandas as pd

In [6]: ci = pd.CategoricalIndex(pd.date_range("2016-01-01 01:01:00", periods=5, freq="D").tz_localize("UTC"))

In [7]: ci
Out[7]: 
CategoricalIndex(['2016-01-01 01:01:00+00:00', '2016-01-02 01:01:00+00:00',
                  '2016-01-03 01:01:00+00:00', '2016-01-04 01:01:00+00:00',
                  '2016-01-05 01:01:00+00:00'],
                 categories=[2016-01-01 01:01:00+00:00, 2016-01-02 01:01:00+00:00, 2016-01-03 01:01:00+00:00, 2016-01-04 01:01:00+00:00, 2016-01-05 01:01:00+00:00], ordered=False, dtype='category')

In [8]: ci_cudf = cudf.from_pandas(ci)

In [10]: ci_cudf
Out[10]: 
CategoricalIndex(['2016-01-01 01:01:00', '2016-01-02 01:01:00',
                  '2016-01-03 01:01:00', '2016-01-04 01:01:00',
                  '2016-01-05 01:01:00'],
                 categories=[2016-01-01 01:01:00, 2016-01-02 01:01:00, 2016-01-03 01:01:00, 2016-01-04 01:01:00, 2016-01-05 01:01:00], ordered=False, dtype='category')
```

Like what is done with `IntervalIndex`, raises a `NotImplementedError` for now to avoid this wrong behavior.

Authors:
  - Matthew Roeschke (https://github.com/mroeschke)

Approvers:
  - Lawrence Mitchell (https://github.com/wence-)

URL: #14032

python/cudf/cudf/core/column/column.py

@@ -2033,9 +2033,19 @@ def as_column(
                     f"{arbitrary.dtype} is not supported. Convert first to "
                     f"{arbitrary.dtype.subtype}."
                 )
-        if is_categorical_dtype(arbitrary):
+        if is_categorical_dtype(arbitrary.dtype):
+            if isinstance(
+                arbitrary.dtype.categories.dtype, pd.DatetimeTZDtype
+            ):
+                raise NotImplementedError(
+                    "cuDF does not yet support timezone-aware datetimes"
+                )
             data = as_column(pa.array(arbitrary, from_pandas=True))
         elif is_interval_dtype(arbitrary.dtype):
+            if isinstance(arbitrary.dtype.subtype, pd.DatetimeTZDtype):
+                raise NotImplementedError(
+                    "cuDF does not yet support timezone-aware datetimes"
+                )
             data = as_column(pa.array(arbitrary, from_pandas=True))
         elif arbitrary.dtype == np.bool_:
             data = as_column(cupy.asarray(arbitrary), dtype=arbitrary.dtype)
@@ -2262,11 +2272,20 @@ def as_column(
     elif isinstance(arbitrary, pd.core.arrays.masked.BaseMaskedArray):
         data = as_column(pa.Array.from_pandas(arbitrary), dtype=dtype)
     elif (
-        isinstance(arbitrary, pd.DatetimeIndex)
-        and isinstance(arbitrary.dtype, pd.DatetimeTZDtype)
-    ) or (
-        isinstance(arbitrary, pd.IntervalIndex)
-        and is_datetime64tz_dtype(arbitrary.dtype.subtype)
+        (
+            isinstance(arbitrary, pd.DatetimeIndex)
+            and isinstance(arbitrary.dtype, pd.DatetimeTZDtype)
+        )
+        or (
+            isinstance(arbitrary, pd.IntervalIndex)
+            and is_datetime64tz_dtype(arbitrary.dtype.subtype)
+        )
+        or (
+            isinstance(arbitrary, pd.CategoricalIndex)
+            and isinstance(
+                arbitrary.dtype.categories.dtype, pd.DatetimeTZDtype
+            )
+        )
     ):
         raise NotImplementedError(
             "cuDF does not yet support timezone-aware datetimes"

python/cudf/cudf/tests/test_datetime.py

@@ -2095,6 +2095,8 @@ def test_construction_from_tz_timestamps(data):
         _ = cudf.Index(data)
     with pytest.raises(NotImplementedError):
         _ = cudf.DatetimeIndex(data)
+    with pytest.raises(NotImplementedError):
+        cudf.CategoricalIndex(data)
 
 
 @pytest.mark.parametrize("op", _cmpops)

python/cudf/cudf/tests/test_interval.py

@@ -167,17 +167,18 @@ def test_interval_index_unique():
     assert_eq(expected, actual)
 
 
+@pytest.mark.parametrize("box", [pd.Series, pd.IntervalIndex])
 @pytest.mark.parametrize("tz", ["US/Eastern", None])
-def test_interval_with_datetime(tz):
+def test_interval_with_datetime(tz, box):
     dti = pd.date_range(
         start=pd.Timestamp("20180101", tz=tz),
         end=pd.Timestamp("20181231", tz=tz),
         freq="M",
     )
-    pidx = pd.IntervalIndex.from_breaks(dti)
+    pobj = box(pd.IntervalIndex.from_breaks(dti))
     if tz is None:
-        gidx = cudf.from_pandas(pidx)
-        assert_eq(pidx, gidx)
+        gobj = cudf.from_pandas(pobj)
+        assert_eq(pobj, gobj)
     else:
         with pytest.raises(NotImplementedError):
-            cudf.from_pandas(pidx)
+            cudf.from_pandas(pobj)